一种适于高维时间序列的特征提取方法(英文)

为了获得更多的信息,越来越多的数据利用多路传感器进行采集,由此产生了大量的超高维时间序列。特征的提取在处理和传输这些数据中起到至关重要的作用。为此,提出一种最优鉴别平面(ODP)技术以消除数据冗余。该平面由两个在Fisher准则基础上建立起来的相互垂直的矢量组成,将模式样本投影到ODP上可得到二维特征矢量。为了衡量特征的有效性,分别用二次判别函数分类器和阈值矢量分类器对特征进行分类测试。同时,以心电信号为例对ODP方法进行测试,结果表明,该方法应用于超高维数据的特征提取是行之有效的。

基于分位数因子模型的高维时间序列因果关系分析

从观察数据中发现变量之间的因果关系是许多科学研究领域的关键问题,传统Granger因果模型受到维度灾难的影响,难以准确地在高维时间序列中发现因果关系.提出一种基于分位数因子模型的Granger因果分析新方法QFMCGC用于高维时间序列因果关系的判定.首先,QFM-CGC采用赤池信息量准则进行模型选择,避免人为干预设置滞后阶数的操作;然后,对向量自回归(Vector Autoregressive,VAR)模型中的条件变量建立分位数因子模型进行降维,减少VAR模型中的待估计系数,对降维后的VAR模型重新进行条件Granger因果分析;最后,使用蒙特卡洛模拟评估不同方法识别底层系统与观测时间序列的连通性结构的能力.在不同维度变量的线性仿真系统和两组现实数据集上与基准方法和经典方法进行了比较,实验结果验证了该方法的有效性.

基于贝叶斯序列分割的高维时间序列在线分类算法

参数化密度估计算法和非参数化密度估计算法均无法高效地处理高维时间序列。针对这种情况,提出基于贝叶斯序列分割的高维时间序列在线分类算法。通过时间延迟嵌入将时间序列投影到重建相位空间,基于贝叶斯序列分割将时间序列分区,结合边际密度和copula变换计算每个区的密度。使用积分平方误差度量时间序列概率密度函数之间的相似性。实验结果表明,该方法对于时间序列的维度具有鲁棒性,能高效地估计时间序列的密度,获得满意的时间序列分类准确率,同时满足在线分类的要求。

高维PP时间序列分析在地震预报中的应用

将投影寻踪(PP)与高维时间序列分析结合起来,建立了地震PP综合预测模型.并选取祁连山地区作研究区,做了未来三个月内最大震级的短期预测.经展望式检验,合格率(预测误差≤0.5或≤10%)≥80%.文中根据实际需要提出建立一定震级门限(M≥4.0)的预测具有更好的效果.本预测模型还可增加自变量、维数和改变时间尺度,并运用到其他领域中.

基于最大熵投票模型的时间序列无监督分割

通过高维时间序列分割可以创建高级符号表示。提出一种针对高维时间序列的无监督分割算法,用于解决高维数据符号化的预处理问题。该算法实现对高维数据的聚类,应用最大熵投票模型进行序列分割。实验结果表明,其平均查全率和查准率分别为0.86和0.88,且整体性能优于主成分分析算法和概率主成分分析算法。

高维静态流体球的Einstein场方程新解

本文给出了高维时空中，静态流体球的爱因斯坦场方程新解。

公交专用道条件下公交车辆轨迹的Seq2Seq预测

即使在公交专用道条件下,因受前方车辆、站台通行能力、行人过街等因素影响,由路段上游到下游停车线持续一定时长的公交车辆轨迹仍然表现出较强的不确定性.简单场景下的单一目标时间序列模型难以有效应对不确定性对公交车辆轨迹预测的影响.针对上述问题,提出将车辆通过路段的整体轨迹表示为由多个相对简单的局部时间序列顺序组成的高维时间序列,应用循环神经网络的单层和多层循环编码器-解码器结构建立高维时间序列中局部序列和整体序列的映射关系,从当前时段轨迹序列开始依次循环预测每个局部序列直到获得未来时段的整体序列.在实验验证中,采用杭州市文三路公交线路的实测GPS轨迹数据对2种结构进行训练和测试.结果表明,所提方法优于现有流行的多步循环序列到序列方法,其中多层结构预测结果和复杂场景的泛化性能均优于单层结构.

NUMERICAL SIMULATIONS OF EVOLUTIONS FROM WALL PULSE TO TURBULENT COHE RENT STRUCTURES

The high order compact d if ference method is developed for solving the perturbation equations based on Navi er Stokes equations, and is used in studying complex evolution processes from w all negative pulse to the turbulent coherent structure in the channel flow. Th is method contains three dimensional coupling difference scheme with high accur acy and high resolution, and the high order time splitting methods. Compared with the general spectral method, the method can be used to research turbule nt coherent structure under more general boundary conditions and in flow domains . In this paper, the generation and evolution of the turbulent coherent structur es ind uced by wall pulse in the channel flow are simulated, and the basic characterist ics and rules of the turbulent coherent structure are shown. Computational r esults indicate that a wall negative pulse is more convenient than the resonant three wave model.

Real-time road traffic states estimation based on kernel-KNN matching of road traffic spatial characteristics

The accurate estimation of road traffic states can provide decision making for travelers and traffic managers. In this work,an algorithm based on kernel-k nearest neighbor(KNN) matching of road traffic spatial characteristics is presented to estimate road traffic states. Firstly, the representative road traffic state data were extracted to establish the reference sequences of road traffic running characteristics(RSRTRC). Secondly, the spatial road traffic state data sequence was selected and the kernel function was constructed, with which the spatial road traffic data sequence could be mapped into a high dimensional feature space. Thirdly, the referenced and current spatial road traffic data sequences were extracted and the Euclidean distances in the feature space between them were obtained. Finally, the road traffic states were estimated from weighted averages of the selected k road traffic states, which corresponded to the nearest Euclidean distances. Several typical links in Beijing were adopted for case studies. The final results of the experiments show that the accuracy of this algorithm for estimating speed and volume is 95.27% and 91.32% respectively, which prove that this road traffic states estimation approach based on kernel-KNN matching of road traffic spatial characteristics is feasible and can achieve a high accuracy.

A novel 3-D spatial temporal channel model for high mobility HAPS-based communications scenario

A high altitude platform station （HAPS） based communications scenario for providing Intemet access and broadband multimedia services to the passengers on board of a high speed train （traveling up to 300km/h） is proposed. Regarding the addressed scenario, when the propagation link between HAPS and train is blocked by obstacles, a three-dimensional （3-D） geometrical single cylinder spatial-temporal channel model is presented, in which closed form, mathematically tractable space-time correlation functions are obtained. It shows that the correlation functions determined by the 3-D model are of significant difference with those of the conventional 2-D model. Based on the analysis model, the paper derives a realized simulation model using sum-of-sinusoids approach, and applies method of equal areas （MEA） and modified method of equal areas （MMEA） to determine the model parameters. The fitting performance of the simulation model with the analysis one is evaluated by two means-square error （MSE） performance criteria. Finally, numerical simulation results verify the mathematical analysis conclusion, when N ≥21, simulation model has an excellent fitness with the analysis one.

PLC应用于喷泉控制系统的方案设计

采用PLC与计算机组成的喷泉控制系统,充分利用PLC的通信功能和编程特点,实现上位机与下位机之间的通信和控制,由远程计算机与PLC之间进行通信,通过PLC实现对喷泉各种水型和灯光的快速控制;另一方面,利用PLC的自诊断功能,可实现喷泉控制系统的故障诊断,不但缩短了维修时间,而且提高了控制系统的稳定性。